Proceedings of the 4th International Conference on Public Management and Intelligent Society, PMIS 2024, 15–17 March 2024, Changsha, China

Research Article

Research on the Influence of Perceived Algorithmic Control on Gig Workers Well-being

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  • @INPROCEEDINGS{10.4108/eai.15-3-2024.2346524,
        author={Biaobin  Yan and Xindan  Zhang and Menghua  Liu},
        title={Research on the Influence of Perceived Algorithmic Control on Gig Workers Well-being},
        proceedings={Proceedings of the 4th International Conference on Public Management and Intelligent Society, PMIS 2024, 15--17 March 2024, Changsha, China},
        publisher={EAI},
        proceedings_a={PMIS},
        year={2024},
        month={6},
        keywords={perceived algorithmic control work engagement employee well-being job demands-resources model},
        doi={10.4108/eai.15-3-2024.2346524}
    }
    
  • Biaobin Yan
    Xindan Zhang
    Menghua Liu
    Year: 2024
    Research on the Influence of Perceived Algorithmic Control on Gig Workers Well-being
    PMIS
    EAI
    DOI: 10.4108/eai.15-3-2024.2346524
Biaobin Yan1, Xindan Zhang1, Menghua Liu2,*
  • 1: Guangdong University of Foreign Studies
  • 2: Guangdong University of Petrochemical Technology
*Contact email: 398198925@qq.com

Abstract

Advocating the humanized management of the platform, improving the satisfaction and well-being of gig works, and increasing their stability and platform stickiness are key issues for the healthy development of the gig economy. Based on the Job Demands-Resources Model, this paper discusses how perceived algorithmic control affects gig workers well-being. We found that, perceived algorithmic control can stimulate the work engagement of gig workers, and then show higher well-being; Work engagement plays a mediating role between perceived algorithmic control and gig workers well-being; Gig worker’ work type (full-time/part-time) plays a moderating effect in the relationship between perceived algorithmic control and work engagement. The research conclusion provides suggestions for online labor platforms to improve the gig workers well-being